Discovering Latent Depression Patterns in Online Social Media
Mental health disorders are a major concern worldwide. However many cases still go undetected. Due to their increasing popularity, online social media sites became promising means to develop innovative methods of detecting such mental disorders. In this work, we present our research towards building automatic early detection systems based on user-generated content. Our experimental results on a real-world dataset reveals evidence that building such systems is viable and can provide promising results.
keywords: Depression, Social Meida
Publication: Congress
1624015056324
June 18, 2021
/research/publications/discovering-latent-depression-patterns-in-online-social-media
Mental health disorders are a major concern worldwide. However many cases still go undetected. Due to their increasing popularity, online social media sites became promising means to develop innovative methods of detecting such mental disorders. In this work, we present our research towards building automatic early detection systems based on user-generated content. Our experimental results on a real-world dataset reveals evidence that building such systems is viable and can provide promising results. - Esteban Andrés Ríssola, David E. Losada, Fabio Crestani
publications_en